In digital imaging systems, color management is the controlled conversion between the color representations of various devices, such as image scanners, digital cameras, monitors, TV screens, film printers, office printers, offset presses, corresponding media, and the like. One primary goal of color management is to obtain a good match across different color devices. For example, a video should appear the same color when displayed on a computer LCD monitor, a plasma TV screen, and on a printed frame of that video. Color management helps achieve a same color appearance across a variety of devices, provided the devices are capable of delivering the needed color intensities. One cross-platform view of color management is the use of an ICC-compatible color management system. The International Color Consortium (ICC) is an industry consortium which defined open standards for a Color Matching Module (CMM) at the OS level, and color profiles for the devices and working space (color space the user edits in).
A color printer destination profile provides a set of device-dependent colorant values (e.g., CMYK) necessary to produce a given color corresponding to a given device-independent color specification (e.g., L*a*b*). For a 4-color (CMYK) printer, this is a three variable to four variable transformation, i.e., transforming L*a*b*→CMYK, which is underdetermined. As a result, there are many device-dependent color specifications for each device-independent color specification. In other words, there is more than one CMYK combination that can produce a given L*a*b*. More combinations are possible when more than 4 colorants are used, e.g., six color CMYKOV. Consequently, in creating a destination profile for a given device, it is often necessary to select one device-dependent color solution out of the several possible solutions for each device-independent color specification. In 4-color printers (CMYK), this selection is often performed by choosing a GCR (Gray Component Replacement) strategy. GCR is a color strategy which relates an amount of CMY to an amount of Black (K). This can lead to a 3-to-3 transformation which has a unique solution. There are, of course, a multiplicity of GCR strategies that can be chosen. Each strategy is equally valid from a colorimetric viewpoint. Applying a fixed GCR strategy does not always provide an optimal solution across the available output gamut of a particular device.
Image spatial noise defects are an image quality problem that generally presents itself as two-dimensional color and/or intensity inconsistencies across an area of an image. Examples of image spatial noise defects are graininess and mottle. Image spatial noise defects are separate from overall color accuracy defects and refer to variations in the intensity and/or color produced by a particular device-dependent color specification. Addressing image spatial noise defects in printing systems has been particularly challenging.
Accordingly, what is needed in this art are increasingly sophisticated systems and methods for selecting an optimum colorant set from the set of available color combinations for a given N-color color device thereby defining a device-dependent color specification that produces a desired device-independent color value while optimizing color image noise and thus improving device performance.